don't index Eigen

1 files changed, 0 insertions, 176 deletions

diff --git a/eigen/test/eigensolver_complex.cpp b/eigen/test/eigensolver_complex.cpp
deleted file mode 100644
index 7269452..0000000
--- a/eigen/test/eigensolver_complex.cpp
+++ /dev/null
@@ -1,176 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-#include <limits>
-#include <Eigen/Eigenvalues>
-#include <Eigen/LU>
-
-template<typename MatrixType> bool find_pivot(typename MatrixType::Scalar tol, MatrixType &diffs, Index col=0)
-{
-  bool match = diffs.diagonal().sum() <= tol;
-  if(match || col==diffs.cols())
-  {
-    return match;
-  }
-  else
-  {
-    Index n = diffs.cols();
-    std::vector<std::pair<Index,Index> > transpositions;
-    for(Index i=col; i<n; ++i)
-    {
-      Index best_index(0);
-      if(diffs.col(col).segment(col,n-i).minCoeff(&best_index) > tol)
-        break;
-      
-      best_index += col;
-      
-      diffs.row(col).swap(diffs.row(best_index));
-      if(find_pivot(tol,diffs,col+1)) return true;
-      diffs.row(col).swap(diffs.row(best_index));
-      
-      // move current pivot to the end
-      diffs.row(n-(i-col)-1).swap(diffs.row(best_index));
-      transpositions.push_back(std::pair<Index,Index>(n-(i-col)-1,best_index));
-    }
-    // restore
-    for(Index k=transpositions.size()-1; k>=0; --k)
-      diffs.row(transpositions[k].first).swap(diffs.row(transpositions[k].second));
-  }
-  return false;
-}
-
-/* Check that two column vectors are approximately equal upto permutations.
- * Initially, this method checked that the k-th power sums are equal for all k = 1, ..., vec1.rows(),
- * however this strategy is numerically inacurate because of numerical cancellation issues.
- */
-template<typename VectorType>
-void verify_is_approx_upto_permutation(const VectorType& vec1, const VectorType& vec2)
-{
-  typedef typename VectorType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-
-  VERIFY(vec1.cols() == 1);
-  VERIFY(vec2.cols() == 1);
-  VERIFY(vec1.rows() == vec2.rows());
-  
-  Index n = vec1.rows();
-  RealScalar tol = test_precision<RealScalar>()*test_precision<RealScalar>()*numext::maxi(vec1.squaredNorm(),vec2.squaredNorm());
-  Matrix<RealScalar,Dynamic,Dynamic> diffs = (vec1.rowwise().replicate(n) - vec2.rowwise().replicate(n).transpose()).cwiseAbs2();
-  
-  VERIFY( find_pivot(tol, diffs) );
-}
-
-
-template<typename MatrixType> void eigensolver(const MatrixType& m)
-{
-  /* this test covers the following files:
-     ComplexEigenSolver.h, and indirectly ComplexSchur.h
-  */
-  Index rows = m.rows();
-  Index cols = m.cols();
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-
-  MatrixType a = MatrixType::Random(rows,cols);
-  MatrixType symmA =  a.adjoint() * a;
-
-  ComplexEigenSolver<MatrixType> ei0(symmA);
-  VERIFY_IS_EQUAL(ei0.info(), Success);
-  VERIFY_IS_APPROX(symmA * ei0.eigenvectors(), ei0.eigenvectors() * ei0.eigenvalues().asDiagonal());
-
-  ComplexEigenSolver<MatrixType> ei1(a);
-  VERIFY_IS_EQUAL(ei1.info(), Success);
-  VERIFY_IS_APPROX(a * ei1.eigenvectors(), ei1.eigenvectors() * ei1.eigenvalues().asDiagonal());
-  // Note: If MatrixType is real then a.eigenvalues() uses EigenSolver and thus
-  // another algorithm so results may differ slightly
-  verify_is_approx_upto_permutation(a.eigenvalues(), ei1.eigenvalues());
-
-  ComplexEigenSolver<MatrixType> ei2;
-  ei2.setMaxIterations(ComplexSchur<MatrixType>::m_maxIterationsPerRow * rows).compute(a);
-  VERIFY_IS_EQUAL(ei2.info(), Success);
-  VERIFY_IS_EQUAL(ei2.eigenvectors(), ei1.eigenvectors());
-  VERIFY_IS_EQUAL(ei2.eigenvalues(), ei1.eigenvalues());
-  if (rows > 2) {
-    ei2.setMaxIterations(1).compute(a);
-    VERIFY_IS_EQUAL(ei2.info(), NoConvergence);
-    VERIFY_IS_EQUAL(ei2.getMaxIterations(), 1);
-  }
-
-  ComplexEigenSolver<MatrixType> eiNoEivecs(a, false);
-  VERIFY_IS_EQUAL(eiNoEivecs.info(), Success);
-  VERIFY_IS_APPROX(ei1.eigenvalues(), eiNoEivecs.eigenvalues());
-
-  // Regression test for issue #66
-  MatrixType z = MatrixType::Zero(rows,cols);
-  ComplexEigenSolver<MatrixType> eiz(z);
-  VERIFY((eiz.eigenvalues().cwiseEqual(0)).all());
-
-  MatrixType id = MatrixType::Identity(rows, cols);
-  VERIFY_IS_APPROX(id.operatorNorm(), RealScalar(1));
-
-  if (rows > 1 && rows < 20)
-  {
-    // Test matrix with NaN
-    a(0,0) = std::numeric_limits<typename MatrixType::RealScalar>::quiet_NaN();
-    ComplexEigenSolver<MatrixType> eiNaN(a);
-    VERIFY_IS_EQUAL(eiNaN.info(), NoConvergence);
-  }
-
-  // regression test for bug 1098
-  {
-    ComplexEigenSolver<MatrixType> eig(a.adjoint() * a);
-    eig.compute(a.adjoint() * a);
-  }
-
-  // regression test for bug 478
-  {
-    a.setZero();
-    ComplexEigenSolver<MatrixType> ei3(a);
-    VERIFY_IS_EQUAL(ei3.info(), Success);
-    VERIFY_IS_MUCH_SMALLER_THAN(ei3.eigenvalues().norm(),RealScalar(1));
-    VERIFY((ei3.eigenvectors().transpose()*ei3.eigenvectors().transpose()).eval().isIdentity());
-  }
-}
-
-template<typename MatrixType> void eigensolver_verify_assert(const MatrixType& m)
-{
-  ComplexEigenSolver<MatrixType> eig;
-  VERIFY_RAISES_ASSERT(eig.eigenvectors());
-  VERIFY_RAISES_ASSERT(eig.eigenvalues());
-
-  MatrixType a = MatrixType::Random(m.rows(),m.cols());
-  eig.compute(a, false);
-  VERIFY_RAISES_ASSERT(eig.eigenvectors());
-}
-
-void test_eigensolver_complex()
-{
-  int s = 0;
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( eigensolver(Matrix4cf()) );
-    s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
-    CALL_SUBTEST_2( eigensolver(MatrixXcd(s,s)) );
-    CALL_SUBTEST_3( eigensolver(Matrix<std::complex<float>, 1, 1>()) );
-    CALL_SUBTEST_4( eigensolver(Matrix3f()) );
-    TEST_SET_BUT_UNUSED_VARIABLE(s)
-  }
-  CALL_SUBTEST_1( eigensolver_verify_assert(Matrix4cf()) );
-  s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
-  CALL_SUBTEST_2( eigensolver_verify_assert(MatrixXcd(s,s)) );
-  CALL_SUBTEST_3( eigensolver_verify_assert(Matrix<std::complex<float>, 1, 1>()) );
-  CALL_SUBTEST_4( eigensolver_verify_assert(Matrix3f()) );
-
-  // Test problem size constructors
-  CALL_SUBTEST_5(ComplexEigenSolver<MatrixXf> tmp(s));
-  
-  TEST_SET_BUT_UNUSED_VARIABLE(s)
-}